بررسی اثر کاربری اراضی در مدل هیدروگراف واحد ژئومورفولوژی مخزن

نوع مقاله : مقالات پژوهشی

نویسندگان

• احمد فاخری فرد
• وحید نورانی
• فائقه نیازی

دانشگاه تبریز

https://doi.org/10.22067/jsw.v30i2.39841

چکیده

پیش بینی سیلاب ها نقش مهمی در برنامه ریزی های هیدرولوژیکی، طراحی ابعاد سازه های هیدرولیکی، مدیریت منابع آب و یا طراحی پایدار نظیر مدیریت و کنترل سیلاب دارد. توسعه سریع حوضه های شهری و افزایش ساخت و ساز و در نتیجه کاهش نقاط نفوذپذیر در سطح حوضه ها باعث توجه بیشتری به هیدرولوژی شهری گردیده است. مدل های هیدروگراف واحد که از تئوری سیستم خطی حاصل می گردند، جهت بررسی اثر شهرسازی بر فرآیند بارش- رواناب مورد استفاده قرار گرفته اند. در این مطالعه اثر کاربری اراضی بر مدل 4GUHCR در نظر گرفته شده و مدل 5GUHRLU ارائه شده است. این مدل ها و مدل مفهومی نش در یک حوضه متشکل از دو زیر حوضه با کاربری اراضی متفاوت، مورد مطالعه قرار گرفته و نتایج آنها با هیدروگراف مشاهداتی مورد مقایسه قرار گرفت. نتایج نشان داد اگرچه مدل های مورد بررسی هیدروگراف را در خروجی حوضه با دقت قابل قبولی پیش بینی می کنند، تنها در مدل ارائه شده GUHRLU به دلیل در نظر گرفتن اثر کاربری اراضی، در خروجی زیر حوضه نتایج مطلوبی حاصل می گردد. مدل گرده ای نش هیدروگراف را تنها در خروجی حوضه محاسبه می کند و هیچ اطلاعی از خصوصیات داخلی حوضه بدست نمی دهد و یک مدل کاملا مفهومی است، لذا بررسی هیدروگراف زیر حوضه ای با استفاده از این مدل امکان پذیر نمی باشد. میانگین معیار نش- ساتکلیف در خروجی زیر حوضه داخلی در مرحله صحت سنجی برای دو مدل GUHCR و GUHRLU به ترتیب برابر 47/0 و 78/0 می باشد. با استفاده از مدل GUHRLU مقادیر خطای دبی پیک و حجم هیدروگراف زیر حوضه ای حدود 40 درصد نسبت به مدل GUHCR بهبود می یابد.

کلیدواژه‌ها

• ژئومورفولوژی
• ضریب ذخیره
• کاربری اراضی
• مدل نش، مدل GUHCR
• مدل GUHRLU
• هیدروگراف داخلی حوضه

20.1001.1.20084757.1395.30.2.24.6

عنوان مقاله [English]

Investigation of Land Use Effects in Geomorphological Unit Hydrograph of Linear Reservoirs

نویسندگان [English]

• Ahmad Fakheri Fard
• Vahid Nourani
• Faegheh Niazi

University of Tabriz

چکیده [English]

Introduction: The influence of urbanization, as one important form of land use, on runoff and floods within watersheds has been a major topic of research during the past few decades. Urbanization affects the hydrology processes of a watershed by replacing the vegetated land cover with impervious surfaces. This can have a substantial effect on the hydrological response of a watershed to rainfall, potentially resulting in faster response, greater magnitude of river flow, higher recurrence of small floods and reduced base-flow, and groundwater recharge. The direct runoff hydrograph generated by rain falling on a watershed reflects the characteristics of both the effective rain hyetograph and the relevant surface features that control the runoff generation and surface-water flow processes.
Materials and Methods: In this study, the effect of land use investigated using GUHCR model and adjusted GUHRLU model is presented. These models and Nash’s conceptual model used to investigate land use impacts for a small, well instrumented watershed consisting of two different land uses sub-watershed in the city of Sierra Vista, Cochise County, Southeastern Arizona. Geomorphological factors for the sub-watersheds extracted by GIS. In this study 13 storm events occurring on both sub-watersheds were selected to examine the proposed model’s performance. Nine events were selected for model calibration. The remaining four events were used to examine the simulated hydrographs for the outlet and the interior natural sub-watershed. The model parameter ( ) was estimated for each event using the moment method and the average of the calibrated values was used for evaluation of the model. The model's performance demonstrated through four popular criteria (i.e. The Nash–Sutcliffe efficiency (NE), the Correlation Coefficient (R), the ratio of the absolute error of peak flow (EP) and the ratio of the absolute error of hydrograph’s volume (Ev)) using available hydro-geomorphological data.
Results and Discussion: The results show that although all studied models forecast the outlet hydrographs with acceptable accuracy, only the presented GUHRLU model shows appropriate results at sub-watershed outlet considering the effect of land use. Clearly, accounting for land use properties in the model formulation leads to improved efficiency at the internal sub-watershed. The Nash model as a lumped model, calculates the hydrography just at the watershed outlet without any information about the hydrological behavior of the interior watershed. Therefore, internal hydrography estimation is impossible via this model. In general, urban runoff tends to have a sharper rising limb and higher peak values while runoffs in natural watersheds have smaller peak values and the rising limb climbs more slowly. The hydrographs show that the overall shapes of the urban sub-watershed hydrographs are similar to each other, while those in the natural sub-watershed tend to be more different, as expected. Simultaneous consideration of geomorphological and land use parameters in the formulation of the proposed model (GUHRLU) provides this capability. As indicated by Ep and Ev, the error of peak flow and the volume of hydrographs show acceptable accuracy. It can be noted that some events show high values of error of peak flows (Ep), however, the model results in small values of Ev that is of great importance in water resource management. Note that, the performance values obtained for the watershed outlet were, for most events, higher than those of the internal sub-watershed outlet in both formulations, which may be due to the use of outlet hydrographs for calculating the model parameter ( )., This might also be due to less uncertainty in urban watersheds where runoff to rainfall ratios is much larger than in the natural sub-watershed. The GUHCR model has slightly better performance at watershed outlet, but it is unable to detect land use variability in its model formulation and so to estimate the internal watershed hydrographs appropriately. Overall, peak discharge and runoff volume for the natural sub-watershed was over-estimated via GUHCR model. The average values for Nash-Sutcliffe criteria at the internal watershed outlet for GUHCR and GUHRLU models are 0.47 and 0.78 respectively. Over 40% improvement is achieved in simulated peak discharge and runoff volume at interior watershed outlet using GUHRLU in compared with GUHCR model.
Conclusion: GUHRLU model considers not only the geomorphologic properties of the watershed, but also the land use variation of the sub-watershed in parameter formulation. This model can also reflect the hydrological conditions of the internal parts of the watershed with divergent land uses. The GUHRLU model is able to improve the efficiency of geomorphological rainfall-runoff simulations at the interior part of the study watershed, located in southeastern Arizona, by taking into account land use. Consideration of land use in the model leads to acceptable results at both watershed and interior sub-watershed outlets, particularly for watersheds like the studied watershed where different land uses sub-watersheds have. The overall efficiency of prediction was slightly poorer for the internal sub-watershed than for the outlet. Application of three models reveals that only the presented GUHRLU model shows appropriate results at sub-watershed outlet in which the land use variation is considered in the model formulation.

کلیدواژه‌ها [English]

• Geomorphology
• GUHCR Model
• GUHRLU Model
• Interior Hydrograph
• land use
• Nash Model
• Storage Coefficient

مراجع

1- Agirre U., Goñi M., Lopez J.J., and Gimena F.N. 2005. Application of a unit hydrograph based on subwatershed division and comparison with Nash's instantaneous unit hydrograph. Catena. 64, 321–332.

2- Bhaskar N.R. 1988. Projection of urbanization effects on runoff using Clark’s instantaneous unit hydrograph parameters. Water Resources Bulletin, 24(1): 113–124.

3- Bonta J.V., Amerman C.R., Harlukowicz T.J., and Dick W.A. 1997. Impact of coal surface mining on three Ohio watersheds—surface water hydrology. Journal of American Water Resources Association, 33(4): 907–917.

4- Boyd M. J., Bufill M. C., and Knee R. M. 1993. Pervious and impervious runoff in urban catchments. Hydrological Sciences Journal, 38(6): 463–478.

5- Chaoqun L., Shenglian G., Zhang W., and Zhang J. 2008. Use of Nash’s IUH DEM’s to identify the parameters of an unequal-reservoir cascade IUH model. Hydrological Process. 22, 4073–4082.

6- Cheng S.J., and Wang R.Y. 2002. An approach for evaluating the hydrological effects of urbanization andits application. Hydrological Processes, 16:1403–1418.

7- Cheng S.J., Lee C.f., and Lee J. H. 2010. Effect of urbanization factors on model parameters. Water Resources Management, 24:775–794.

8- Cheng S.J. 2011. The best relationship between lumped hydrograph parameters and urbanization factors. Natural Hazards, 56:853–867.

9- Chow V.T., Maidment D.R., and Mays L.W. 1988. Applied Hydrology. McGraw-Hill, New York, USA.

10- Dougherty M., Dymond R.L., GrizzardJr T.J., Godrej A.N., Zipper C.E., and Randolph J. 2006. Quantifying long term hydrologic response in an urbanizing basin. Journal of Hydrologic Engineering, 12: 33–41.

11- Ferguson B.K., and Suckling P.W. 1990. Changing rainfall–runoff relationships in the urbanizing Peachtree Creek watershed, Atlanta, Georgia. Water Resources Bulletin, 26(2): 313–322.

12- Hollis G.E. 1975. The effect of urbanization on floods of different recurrence interval. Water Resources Research, 11: 431–435.

13- Huang H.J., Cheng S.J., Wen J.C., and Lee J.H. 2008. Effect of growing watershed imperviousness on hydrograph parameters and peak discharge. Hydrological Process. 22, 2075– 085.

14- Huang S.Y., Cheng S.J., Wen J.C., and Lee J. H. 2012. Identifying hydrograph parameters and thei relationship to urbanization variables. Hydrological Sciences Journal, 57:144–161.

15- Jones J. A., and Grant G. E. 1996. Peak flow responses to clear-cutting and roads in small and large basins, western Cascades, Oregon, Water Resources Research. 32(4), 959–974.

16- Kang I.S., Park J.I., and Singh V.P. 1998. Effect of urbanization on runoff characteristics of the On-Cheon Stream watershed in Pusan, Korea. Hydrological Processes, 12: 351–363.

17- Kennedy J. R., Goodrich D.C., and Unkrich C.L. 2013. Using the KINEROS2 Modeling Framework to Evaluate the Increase in Storm Runoff from Residential Development in a Semiarid Environment. Journal of Hydrologic Engineering, 18: 698-706.

18- Moscrip A.L., and Montgomery D.R. 1997. Urbanization flood frequency, and salmon abundance in Puget Lowlan Streams. Journal of the American Water Resources Association, 33(6): 1289–1297.

19- Nash J.E. 1957. The form of the instantaneous unit hydrograph .Hydrology Sciences Bulletin, 3: 114-121.

20- Nash J.E., and Sutcliffe J.V. 1970. River flow forecasting through conceptual models I: a discussion of principles. Journal of Hydrology, 10(3): 282–290.

21- Ng H.Y.F., and Marsalek J. 1989. Simulation of the effects of urbanization on basin streamflow. Water Resources Bulletin, 25(1): 117–124.

22- Nourani V., Singh V.P., and Delafrouz H. 2009. Three geomorfologicalrainfall–runoffmodels based on the linear reservoir concept. Catena,76: 206–214.

23- Rodriguez-Iturbe I., and Valdes J.B. 1979. The geomorphologic structure of the hydrologic response, Water Resources Research. 15(6), 1409-1420.

24- Shuster W., Bonta J., Thurston H., Warnemuende E., and Smith D. 2005. Impacts of impervious surface on watershed hydrology: A review. Urban Water Journal, 2(4): 263–275.

25- Singh V.P. 1988. Hydrologic Systems. Rainfall–Runoff Modeling, vol. I. Prentice-Hall, Englewood Cliffs.

26- Tsihrintzis V.A., and Hamid R. 1997. Urban stormwater quantity/quality modeling using the SCS method and empirical equations. Journal of the American Water Resources Association, 33 (1): 163–176.

27- Tung Y.K., and Mays L.W. 1981. State variable model for urban rainfall–runoff process. Water Resources Bulletin, 17(2): 181–189.

28- U.S. Dept. of Agriculture (USDA). 1986. Urban hydrology for small watersheds: Technical Release 55, Washington, DC.

29- Wagener T. 2007. Can we model the hydrological impacts of environmental change? Hydrological Processes 21(23): 3233–3236.